Prevalence of diabetic kidney disease and the associated factors among patients with type 2 diabetes in a multi-ethnic Asian country

The actual prevalence of diabetic kidney disease (DKD) in patients with type 2 diabetes (T2D) in Malaysia is unknown. We aimed to determine the prevalence of DKD and its associated risk factors among T2D patients in Malaysia. An analytical cross-sectional study was conducted using the year 2022 clinical audit dataset from the National Diabetes Registry. DKD was defined as albuminuria, a decreased glomerular filtration rate, or both. Among 80,360 patients, 62.2% were female, 68.4% were Malay, and the mean age was 61.4 years. A total of 56.7% (95% CI 56.4–57.1%) of patients were found to have DKD. Increasing age, male sex, Malay ethnicity, longer duration of diabetes, overweight, obesity, hypertension, diabetic retinopathy, diabetic foot ulcer, nontraumatic lower-extremity amputation, ischaemic heart disease, stroke, insulin, higher numbers of antihypertensive agents, antiplatelet agents, poorer HbA1c control, higher systolic blood pressure, non-achievement of triglyceride target, and non-attainment of HDL-cholesterol goal were independent risk factors associated with DKD. Clinicians, program managers, and health policymakers should target modifiable factors to manage DKD and prevent its progression to end-stage kidney disease in Malaysia.


Study population
The target population included patients with T2D who received care from public health clinics in Malaysia.Around 70% of patients with diabetes in the country were treated in public health clinics 16 .The inclusion criteria were adult patients with T2D aged 18 years and above.Patients without documented serum creatinine or urine albumin levels were excluded.Figure 1 shows the flow diagram detailing the number of individuals at each stage of the dataset management, together with inclusion and exclusion criteria.The final number of eligible patients for analysis was 80,360.We compared the proportions of selected and non-selected patients by demographic factors in Supplementary Table S1.A higher proportion of those selected in the study were in the younger age category, females, and of Malay ethnicity.

Dependent variable
DKD was defined as having albuminuria, a decreased GFR, or both 4 .We defined albuminuria as having macroalbuminuria and/or microalbuminuria.Macroalbuminuria and microalbuminuria were captured as categorical variables with positive or negative results, respectively, in the audit dataset.The test for microalbuminuria was routinely done in T2D patients having negative results for urine protein.Common tests used to detect albuminuria in health clinics included automated urine analysis, dipstick, 24-h urine protein, and urine albumin-tocreatinine ratio 17 .

Independent variables
The independent variables included demographic factors, comorbidities, diabetes-related complications, pharmacological treatments, and metabolic control.The demographic characteristics included age, sex, and ethnic groups.Besides the three major ethnicities (Malay, Chinese, and Indian) in Malaysia, there are indigenous people of Bumiputera Sabah and Bumiputera Sarawak who mainly reside in East Malaysia.'Other ethnic groups' comprised minority ethnicities such as indigenous people of Peninsular Malaysia and those of foreign nationals.Smoking status was defined as the current smoking status.
Overweight and obesity categories were classified as having body mass index (BMI) of 23.0-27.4and ≥ 27.5 kg/ m 2 , respectively 22 .These lower cut-offs followed the World Health Organization (WHO) recommendations for Asian populations due to their greater risks of adverse cardiovascular outcomes 23 .Meanwhile, hypertension and dyslipidaemia followed clinical diagnoses or the use of corresponding pharmacological agents.Diabetesrelated complications, such as diabetic retinopathy, diabetic foot ulcer, nontraumatic lower-extremity amputation, ischemic heart disease, and stroke, were based on clinical diagnoses by treating doctors.
Diabetes treatment modality was categorised as 'lifestyle management only' , 'oral glucose-lowering drug (OGLD) only' , 'insulin only' , and 'OGLD and insulin' .Hypertension treatment was categorised as zero, one, two, and ≥ three blood pressure-lowering drugs.The usage of lipid-lowering and antiplatelet agents was also described.
The metabolic control covered glycosylated haemoglobin A1c (HbA1c), blood pressure (BP), and LDLcholesterol, the three primary treatment targets in diabetes management 20 .Most patients with T2D had a HbA1c target < 7.0%, while others, such as elderly patients and those with comorbidities, including DKD, were recommended to achieve a HbA1c goal between 7.0 and 8.0% 20 .Patients with HbA1c > 8.0% were considered to have poor glycaemic control 20 .The BP were classified according to stage I (140-159/90-99 mmHg), stage II (160-179/100-109 mmHg), and severe hypertension (≥ 180/ ≥ 110 mmHg) 24 .An additional systolic BP cutoff of 130 mmHg was used because BP < 130/80 mmHg was the individualised treatment target for patients with DKD or cardiovascular diseases 20 .Otherwise, a BP < 140/80 mmHg was aimed at those without DKD or cardiovascular diseases 20 .The LDL-cholesterol < 2.6 mmol/L was the general target, while an intensified LDLcholesterol < 1.4 mmol/L was recommended for those with target organ damage, including DKD 20 .
The secondary treatment targets, namely triglyceride and HDL-cholesterol, were also reported 20 .The triglyceride target was < 1.7 mmol/L, and HDL-cholesterol targets were > 1.0 for males and > 1.3 mmol/L for females 20 .

Statistical analysis
The analysis was carried out using the IBM SPSS Statistics version 23.Descriptive data were presented as frequencies with percentages for categorical variables.Whereas, mean ± standard deviation or median (interquartile range) were reported for continuous variables.The proportion of patients with DKD was presented as frequency and percentage with a 95% confidence interval.We first performed bivariate analyses.Differences between DKD status were assessed using Pearson chi-square tests for categorical variables, Student's t-tests for means, and Mann-Whitney tests for medians.Then, multivariate binary logistic regression was carried out for independent variables with P values < 0.25 and clinically essential variables to determine factors associated with DKD.A forward stepwise likelihood ratio was used.The classification table, coefficient of determination, Omnibus test of model coefficients, Hosmer-Lemeshow test, and area under receiving operating characteristics (ROC) curve were reported.We also assessed multicollinearity and the interaction between variables.P values, adjusted odd ratios, and 95% confidence intervals were presented.The statistical significance threshold was pre-set at P < 0.05.All missing data were list-wise deleted in the multiple logistic regression analysis as we intend to analyse the realworld clinical data as it is.Demographic differences between patients selected in the study and those included in the multiple logistic regression analyses were compared using Chi-square tests.

Ethical approval
This research was approved by the Medical Review and Ethics Committee of the Ministry of Health Malaysia (NMRR ID-23-01030-S6L).The Medical Research and Ethics Committee waived the requirement for informed consent because this study used secondary data without personal identifiers.All methods followed the Declaration of Helsinki and the Malaysian Good Clinical Practice Guidelines.

Characteristics of patients with diabetic kidney diseases
Patients with DKD were significantly older, male, of Malay ethnicity, current smokers, and had been diagnosed with diabetes for a longer duration (Supplementary Table S2).Patients with DKD generally had a higher mean body mass index (BMI), and a higher proportion of them were underweight and obese.DKD was associated with all the comorbidities and complications studied.More patients had hypertension, dyslipidaemia, diabetic retinopathy, diabetic foot ulcers, nontraumatic lower-extremity amputation, ischemic heart disease, and stroke.Correspondingly, a higher proportion of patients with DKD were treated with insulin, antihypertensive, lipidlowering agents, and antiplatelet agents.
Patients with DKD had higher mean HbA1c levels.Despite having a less stringent HbA1c target, 40.5% had uncontrolled HbA1c levels > 8.0%.Meanwhile, a higher proportion of patients with DKD had high systolic and diastolic BP.Thus, lower proportions achieved BP < 140/80 mmHg and < 130/80 mmHg.Among those with DKD, only 10,807 (23.9%) patients achieved a more stringent treatment goal of < 130/80 mmHg.
A higher proportion of patients with DKD had LDL-cholesterol < 2.6 and < 1.4 mmol/L.Among the patients with CKD, only 6.0% achieved a more stringent LDL-cholesterol target of < 1.4 mmol/L.Patients with DKD had a higher mean triglyceride level, with a correspondingly lower proportion attaining the target triglyceride level.Meanwhile, patients with DKD had a lower mean HDL-cholesterol level with a lower proportion achieving the HDL-cholesterol goal.www.nature.com/scientificreports/

Factors associated with diabetic kidney disease
Eighteen independent factors were associated with DKD, as shown in Table 2. Increasing age, longer duration since diabetes diagnosis, overweight, obesity, hypertension, diabetic retinopathy, diabetic foot ulcer, nontraumatic lower-extremity amputation, ischaemic heart disease, stroke, insulin (alone and in combination with oral glucoselowering drugs), higher numbers of antihypertensive agents, antiplatelet agents, poorer HbA1c control, and higher systolic BP categories were associated with higher odds ratios for DKD.In contrast, females and patients attaining triglyceride and HDL targets were less likely to have DKD.There were ethnic variations; Chinese, Indian, Bumiputera Sarawak, and other ethnicities had lower adjusted odds ratios than the Malay ethnic group.Supplementary Table S3 compares the demographic characteristics of included and non-included patients in the multiple logistic regression analysis.A higher proportion of those included were in the younger age category, females, and of Malay ethnicity.

Discussion
More than half of our patients with T2D had DKD, and this prevalence falls between the 27.1% to 83.7% range reported worldwide 5 .This wide range of prevalence could be due to differences in DKD definition, patient profiles, healthcare settings, and health systems 5,25 .Our result closely approximates the global prevalence (56%) reported in the DEMAND (Developing Education on Microalbuminuria for Awareness of renal and cardiovascular risk in Diabetes) study 1,26 .Moreover, the composition of DKD by reduced eGFR and positive albuminuria among our patients is also similar to the global average; most DKD diagnoses are due to albuminuria with normal eGFR, followed by reduced eGFR and positive albuminuria, and finally, non-proteinuric kidney disease 1,26 .Indeed, a review article reported that non-proteinuric rather than proteinuric kidney diseases are the leading cause of ESKD, and non-proteinuric DKD prevails over the proteinuric form among T2D diabetes 27 .
Our prevalence of DKD is also comparable with 53% reported in a Singaporean study among a multi-ethnic group of primary care patients with T2D 25 .Again, the composition of DKD is similar to ours: 21% of their patients had reduced eGFR, while 48% had albuminuria 25 .The breakdown by GFR categories from stage G3a to G5 was also comparable with our study 25 .Besides that, a similar prevalence of reduced GFR and prevalence by GFR stages were reported in northern Thailand among T2D patients in the primary care setting 28 .
Overall, DKD is a common complication in patients with T2D in Malaysia.These results have important clinical and public health implications.Clinically, it implies the need to manage patients more aggressively to prevent the progression to ESKD, especially since diabetes was already the main contributor to dialysis in Malaysia 10,20 .DKD screening activities must also be intensified urgently, particularly because many patients in early DKD are asymptomatic and called the 'silent majority' 6 .The clinical practice guidelines recommend screening for DKD during the initial visit and annually thereafter 20 .The lack of adherence to these recommendations constitutes clinical inertia that must be managed appropriately 29 .The WHO has recently recommended monitoring the proportion of diabetes patients with DKD in healthcare facilities, which should be considered in our health clinic settings to ensure optimal patient and programme monitoring 14 .
From a public health standpoint, the high DKD burden should alert health policymakers and programme managers about the substantial financial costs and adverse health outcomes associated with the disease, such as frailty, ESKD, reduced quality of life, and premature deaths 1 .The problem will only be magnified if more Malaysians develop diabetes, and if diabetes control remains unattainable among existing patients, more of them will end up having ESKD 20 .Around 106,000 dialysis patients are projected in Malaysia by the year 2040 30 , and the relative high share of ESKD health expenditure in the public sector will stress the financing mechanism of the disease 31 .Therefore, primary, secondary, and tertiary prevention of diabetes must be optimised to tackle  www.nature.com/scientificreports/ the diabetes epidemic in Malaysia.This effort is consistent with the National Action Plan for Healthy Kidneys 2018-2025, a strategic plan to decrease CKD burdens in the country 32 .
Established risk factors for DKD can be divided into non-modifiable and modifiable risk factors 1,5 .Our study findings are consistent with increasing age, male sex, ethnicity, and long duration of diabetes as non-modifiable factors associated with DKD 1,5 .Previous studies reported ethnic differences with Asian, Hispanic, and indigenous Australians tend to have a higher prevalence of DKD than Caucasians 1 .Further, Asian participants were found to have the highest proteinuria compared to Hispanic, African, Caucasian, and other ethnic groups 26 .The reasons for ethnic variations in DKD are complex and multifactorial 1 .The factors include genetic factors and developmental programming, age of T2D onset, lifestyle factors, socioeconomic disadvantages, access to and uptake of care, inadequate screening rates, and poorer attainment of treatment targets 1 .
Our multi-ethnic populations in Malaysia confer an advantage in observing ethnic variations in the prevalence of DKD.However, it is unclear why the Malay ethnicity is more likely to be associated with DKD.Further research is recommended to investigate the underlying reasons for the observed ethnic differences in Malaysia.
Obesity, hypertension, poor glycaemic control, poor blood pressure control, and lipid abnormalities are known modifiable risk factors for DKD, and our study again showed consistent findings 1,5 .These results further emphasise the crucial need to optimise body weight and control metabolic targets among T2D patients.However, most of our patients with DKD did not achieve HbA1c, intensified BP, or intensified LDL-cholesterol goals.This is alarming because inadequate metabolic control can lead to the progression of DKD to ESKD 1 .Moreover, poor control of these risk factors will increase the competing risk of premature mortality, mainly due to cardiovascular diseases 1 .
We also found that diabetic retinopathy, diabetic foot ulcer, nontraumatic lower-extremity amputation, ischaemic heart disease, stroke, insulin, antiplatelet agents, and higher numbers of antihypertensive agents were associated with DKD.All these factors are proxies for more severe diabetes conditions and are clinically logical to be related to DKD.Similar associations have been reported in other epidemiological studies among patients with T2D in Singapore, Thailand, Hong Kong, and Italy 25,28,33,34 .Interestingly, we found that underweight patients were independently associated with DKD; the adjusted odds ratio was even higher than that for obesity.A Korean nationwide cohort study reported that the underweight BMI category was an independent risk factor for ESKD among patients with diabetes 35 .Moreover, those with weight loss > 10% had the fastest decline in kidney function 35 .Some plausible mechanisms include sarcopenia and oxidative DNA damage associated with weight loss 35 .
We acknowledge missing data as a limitation in this registry-based study.We noted that a higher proportion of patients selected for this study and those included in the regression analysis were females, in the younger age category, and of Malay ethnicity, and this could cause selection bias and distort the actual prevalence of DKD in this study.As increasing age and male sex are established non-modifiable risk factors for DKD 1,5 , our study sample could have pulled the DKD prevalence downwards.In other words, the actual prevalence of DKD among T2D patients in Malaysia could be higher if more males and older patients were included.In contrast, since we found that the Malay ethnicity was more likely to have DKD, a higher proportion of Malay patients could have pushed the prevalence upwards.Nevertheless, our current prevalence estimate is still valid based on available real-world clinical data, with the prevalence falling between the range reported worldwide and similar to our neighbouring countries in Singapore and Thailand 5,25,28 .
This study has other limitations.The cross-sectional design disallows any causal inference between DKD and the associated factors.Measurement errors can occur because of the lack of standardisation mechanisms between health clinics across Malaysia.Nevertheless, the data reflect real-world clinical scenarios.Besides that, the analysis was limited to the data available in the National Diabetes Registry.Uncaptured information, such as socioeconomic disadvantages, family history of DKD, previous episodes of acute kidney injury, and inflammatory markers, all associated with DKD, could not be investigated in this study 5 .We were also unable to quantify the level of albuminuria as the details were not captured in the database.Our study definition of DKD was based on a single positive reading of albuminuria, a decreased GFR, or both with no repeated measurement typically taken 3 months apart to confirm the chronic nature of CKD 18 .Nevertheless, our results are still valid with similar www.nature.com/scientificreports/definitions employed in other cross-sectional studies with no repeated measures to determine CKD or DKD prevalence 25,28,36,37 .Finally, the study population was confined to T2D patients in public health clinics; hence, the results cannot be generalised to patients treated in hospitals and those with type 1 diabetes.
To our best knowledge, this nationwide study is among the first to report the prevalence of DKD and its associated factors among patients with T2D in Malaysia.Real-world clinical information offers the added advantage of depicting the actual situations in the field.Our results have established a baseline prevalence of DKD among T2D patients in Malaysia, which may aid in monitoring the WHO indicator for DKD 14 .This study uncovers a high prevalence of DKD with important clinical and public health implications, as discussed above.We hope the results will help inform policymaking and the development of clinical practice guidelines in the country.This study also benefitted from the multi-ethnic population in Malaysia.The observed ethnic differences in the prevalence of DKD may provide an impetus for new studies on kidney complications among multi-ethnic diabetes patients to improve clinical outcomes.
In summary, DKD is highly prevalent among T2D patients in Malaysia.Increasing age, male sex, Malay ethnic group, longer duration of diabetes, overweight, obesity, hypertension, diabetic retinopathy, diabetic foot ulcer, nontraumatic lower-extremity amputation, ischaemic heart disease, stroke, insulin, higher numbers of antihypertensive agents, antiplatelet agents, poorer HbA1c control, higher systolic BP, non-achievement of triglyceride target, and non-attainment of HDL-cholesterol goal are independent factors associated with DKD.Clinicians, program managers, and health policymakers should target these modifiable factors to manage DKD and prevent its progression to ESKD.

Figure 1 .
Figure 1.Flow diagram detailing the number of individuals at each stage of the dataset management, together with inclusion and exclusion criteria.

Figure 2 .
Figure 2. Prevalence of diabetic kidney disease based on glomerular filtration rate and albuminuria.eGFR: estimated glomerular filtration rate.

Table 2 .
Factors associated with diabetic kidney disease.The number of patients included in this analysis was 67,368, with 12,992 (16.2%) not included.The model was valid because the Hosmer and Lemeshow test was insignificant, P = 0.08.The model improved over the baseline model, as the Omnibus test was significant, P < 0.001.The coefficient of determination (R 2 ) was 0.122, and the overall correct percentage was 63.0% in the classification table.The area under the receiving operating characteristics (ROC) curve was 0.673 (95% CI 0.669-0.677),P < 0.001.HbA1c: glycosylated haemoglobin A1c; HDL-C: HDL-cholesterol; OGLD: oral glucose-lowering drug.